THz Connect: Energy-Efficient 6G Small Cells With Fuzzy Power Control and Advanced Clustering
The increasing number of users in 6G networks requires more base stations. Mobile small cell BSs solve this but complicate the power allocation and clustering, which becomes even more challenging with a dynamic system topology as the user density increases. Computational Intelligence-based systems c...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Open Journal of the Communications Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10965731/ |
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| Summary: | The increasing number of users in 6G networks requires more base stations. Mobile small cell BSs solve this but complicate the power allocation and clustering, which becomes even more challenging with a dynamic system topology as the user density increases. Computational Intelligence-based systems can support addressing this problem via the learning-based mechanism for making near-optimal decisions. In this paper, we combine mobile BS, THz communication, massive multiple input multiple outputs (mMIMO), non-orthogonal multiple access (NOMA), and device-to-device (D2D) technologies in a 6G HetNet environment. We propose a power allocation and clustering scheme to maximize the sum rate of the proposed 6G mobile small cell system. First, we propose a green 6G mobile small-cell model with the help of THz, NOMA, and D2D. Then, a novel fuzzy logic system that exploits channel gains to design optimum power allocation in NOMA is proposed. Further, we propose an advanced clustering scheme that effectively integrates user device energy, proximity, and antenna parameters to reduce interference and enhance the energy efficiency of MSBS. |
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| ISSN: | 2644-125X |